Abstract
Forests play a vital role in sequestering CO2 from the atmosphere and storing it as wood, and the 3D structure of these ecosystems provides crucial habitat for biodiversity. Canopy-dominant trees contribute disproportionally to forest carbon sequestration and storage, as well as shaping the 3D structure of these ecosystems. However, the factors that drive variation in the size and shape of the crowns of canopy-dominant trees across different forest ecosystems remain poorly understood. Traditionally, ecologists have relied on field data to measure and model variation in tree size and shape using allometric functions that predict one attribute (e.g., height, crown diameter or biomass) from other attributes that are easier to measure (e.g., stem diameter). But this presents an inherent challenge for canopy-dominant trees, as they only make up a small proportion of stems in a plot and their crown attributes are challenging to measure accurately from the ground due to occlusion in the canopy. Recent developments in remote sensing, in particular airborne laser scanning (ALS), have transformed our ability to capture information about the size and shape of the crowns of canopy-dominant trees across large spatial scales. And yet, we continue to lack a global assessment of the drivers that underpin the enormous variation in tree crown size and shape we observe in nature.To address this knowledge gap, we used ALS to directly measure tree height, crown area, crown shape and height-to-crown scaling relationships of canopy-dominant trees from above. Specifically, we compiled co-located ALS and RGB imagery at 25 sites spanning all major forest types and used these to manually delineate the crowns of >30,000 canopy-dominant trees. Using this unique dataset, we explored how crown area–tree height scaling relationships and crown symmetry vary within and between forest types in relation to climate, disturbance, topography, and local competitive environment. We found climatic variables to be the key driver of broad-scale differences in crown architecture across forest types, and local factors such as competition and disturbances were important in explaining the variation of crown symmetry among individual trees. Interestingly we found topographic variables to have little to no effect on crown architecture in a global context. Crucially, we also show that the crown architecture of canopy-dominant trees is poorly predicted using existing allometric databases compiled from field data, as they are systematically biased towards smaller trees. Our study takes a key step towards better representing the spectrum of crown architectures that characterise the world's canopy-dominant trees, with important implications for integrating forest monitoring programs with remote sensing and forest models.
| Date of Award | 23 Jan 2024 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Tommaso Jucker (Supervisor) & Martin De Kauwe (Supervisor) |